The Product Recommendation System for Home Appliances is an e-commerce platform designed to enhance the shopping experience by providing personalized product recommendations to customers. This system allows customers to browse a wide range of home appliances, add them to their cart, and make purchases. Shop owners can register and add products, which are displayed on the platform after admin approval. The system uses a content-based filtering approach to recommend products based on their textual descriptions. When a customer views a product, the system analyzes its description and suggests similar items using TF-IDF (Term Frequency-Inverse Document Frequency) and Cosine Similarity algorithms. This improves product discovery and increases the likelihood of a purchase. The project consists of three main modules: the Admin Panel for managing shop owner requests, the Shop Owner Panel for adding and managing products, and the Customer Panel for browsing products, receiving recommendations, and completing transactions. The platform aims to offer a seamless, user-friendly experience, leveraging machine learning to provide relevant suggestions and enhance customer satisfaction. Future enhancements include expanding the recommendation system and integrating collaborative filtering for even more personalized recommendations.